This book provides a comprehensive overview of current practices and future directions in airline revenue management. It explains state-of-the-art revenue management approaches and outlines how these will be augmented and enhanced through modern data science and machine learning methods in the future. Several practical examples and applications help to familiarize the reader with the relevance of the corresponding ideas and concepts for a commercial airline organization. The book is ideal for both students in the field of airline and tourism management as well as for practitioners and industry experts seeking to refresh their knowledge about current and future revenue management approaches and to gain an introductory understanding of data science and machine learning methods. Each chapter closes with a checkpoint, allowing the reader to deepen their understanding of the contents covered.Contents
- Fundamentals of airline revenue management- Computerized revenue management- Estimation and forecasting- Optimization, types of control and overbooking- Network revenue management- Ancillary revenues- Data science and revenue management
About the authorsAndreas Thams is an Honorary Professor for Airline Management at University of Applied Sciences Worms. He held various commercial management positions in the airline, travel and logistics industry, particularly in the field of revenue management. He has a Ph.D. in Econometrics from Freie Universitt Berlin.Curt Cramer is an Advanced Analytics and Data Science executive in the retail industry. He has gathered extensive applied analytics experience in 15 years of consulting and line management responsibilities across industries, including leisure travel. He holds a Ph.D. in Engineering/Computer Science from the University of Karlsruhe/KIT.